[R] Actual vs. predicted survival times

[Bonnett, Laura]

Dear R-help,

I am using R 2.14.1 on Windows 7.

I would like to produce a plot like the attached - although simplified to actual vs. Predicted survival time with distinguishing marks for censored and observed points.  I have a dataset and have fitted a Cox model to it.  In an attempt to visualise how accurate the model is it would be ideal if I could plot the actual survival times against the predicted survival times.

I have been looking on the internet to see if there are ways to do this in R.  The only post I found (https://stat.ethz.ch/pipermail/r-help/2009-February/189888.html) that seemed directly relevant suggested that I shouldn't be generating survival times at all.  Given that, I was concerned about proceeding but I would like to have access to a plot to make a decision on its usefulness.

I appreciate that there are predict.coxph and predict.cph options available to me.

My first attempt was as follows:

# fit Cox model #
coxfita = coxph(Surv(tsecond,seccens)~stroke(smess)+rels(smess)+asleep(smess)+eeg1(smess)+eeg2(smess)+ct1(smess)+ct2(smess)+treat(smess),data=smess)

# Find censored and observed groups #
messcens <- subset(smess,seccens==1)
messobs <- subset(smess,seccens==0)

# Obtain predicted survival times #
explp <- exp(predict(coxfita,type="lp"))
explp2 <- mean(ssmess$tsecond,na.rm=TRUE)*explp
smess2 <- data.frame(ssmess,explp2)

# Find censored and observed groups #
smesscens <- subset(smess2,seccens==1)
smessobs <- subset(smess2,seccens==0)

# Produce plot #
plot(smesscens$explp2,messcens$tsecond,pch=4,col="blue",ylab="Actual Survival Time",xlab="Predicted Survival Time",main="Survival Times",xlim=c(0,3500),ylim=c(0,3500))
points(smessobs$explp2,messobs$tsecond,pch=4,col="red")

This leads to the attached plot.  It doesn't seem correct though as the predicted times all start over 500 days.

Any suggestions would be very welcome.

Many thanks,
Laura

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